PROJECT SUMMARY Sleep and circadian rhythms play critical roles in the maintenance of physical and mental health, with disturbances in these domains associated with major public health consequences. Despite the abundance of epidemiological evidence linking sleep and circadian traits to diverse pathologies, little is known about the genetic factors that underlie these traits. Sleep and circadian traits, such as insomnia and chronotype, are highly heritable and aggregate in families, suggesting a substantial proportion of risk is due to genetics. Progress has been made in identifying risk variants for these traits using genome-wide association studies (GWAS). However, GWAS results principally reside in non-coding regions of the genome and rarely pinpoint the precise location of the actual effector genes. Mounting evidence is indicating that simply attributing GWAS signals to the genes encoded in the closest genomic regions is not always accurate. As such, GWAS alone is primarily beneficial to signal discovery, not functional gene discovery. The difficulty in elucidating the actual effector genes for human GWAS signals is a significant barrier to identifying novel molecular regulators of sleep. Despite wide-ranging tools utilizing model systems and in vitro approaches to conduct such functional analyses, as well as computational methods to implicate causal variants, these approaches are underutilized in the sleep and circadian domain. This proposal seeks to fill this critical knowledge gap by employing a team science approach, bringing together expertise in the genomics of sleep and circadian rhythms that spans humans, model systems, and computational biology, while simultaneously leveraging large existing datasets for genetic discovery. In Aim 1, we will leverage existing biobank data for discovery of risk variants for insomnia and chronotype. This will be followed, in Aim 2, by examination via a battery of spatial genomic analyses of these loci using IPSC-derived neuro progenitor cells to identify causal variants. Finally, we will determine which genes have functional relevance using Drosophila as a model system. Our global hypothesis is that genomic variation is strongly associated with the behavioral manifestation of insomnia and chronotype and that our cutting-edge molecular approaches will elucidate the causal variants and the corresponding effector genes at these loci. We aim to translate genetic information into meaningful benefits for patient care by uncovering the correct functional context of GWAS identified genomic variants involved in these traits and understanding how they operate in this context.